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Uber

Sr Software Engineer - Location & Sensors

Posted 20 Days Ago
Be an Early Applicant
In-Office
San Francisco, CA, USA
202K-224K Annually
Senior level
In-Office
San Francisco, CA, USA
202K-224K Annually
Senior level
Develop location platform software, APIs, sensor-processing systems, geospatial capabilities, and data pipelines supporting machine learning workflows. Improve location accuracy through distributed systems, predictive modeling, and sensor fusion. Document algorithms and architectures while collaborating with engineering teams to enhance Uber’s location services.
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About the Role

As a Software Engineer on the Location & Sensors team, you will play a crucial role in developing Uber's Location Platform to further enhance Uber's geospatial capabilities. The Location & Sensors team is focused on improving location accuracy and sensor data processing to power various Uber products and services. You will work on projects related to location data analysis, sensor fusion, and predictive modeling. This work directly impacts the efficiency and reliability of Uber's core operations, including moving people, food, and groceries from point A to point B.

Basic Qualifications
  • A Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field. Masters preferred. 
  • 5+ years of experience in professional software development experience, developing and deploying systems in production environments
  • Knowledge of different compilation steps (and ability to fix) in languages such as Go, C, C++, or Java.
  • Excellent written and verbal communication skills, including the ability to document architectures and algorithms. 
  • Experience with Software Engineering Best Practices.
Preferred Qualifications
  • Experience with geospatial data and location-based services
  • Familiarity with sensor data processing and analysis
  • Experience with Go, Java
  • Experience with distributed systems
  • Experience with big data pipelines like Flink and Spark
What You Will Do
  • Develop and implement APIs to serve Location and Inferences
  • Collaborate with the team to improve location accuracy and sensor data processing.
  • Design and build data pipelines to support machine learning workflows.
  • Design and Develop improvements to Uber's location accuracy
  • Document novel algorithms for improving Uber's location coverage.
Responsibilities

For San Francisco, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.

You will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.

About Us

Ready to Ride?

This isn't the kind of place where you follow a playbook — it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves — we'd love to hear from you.

You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits.

Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements.

Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.

HQ

Uber San Francisco, California, USA Office

Uber's a hybrid work environment and employees target spending 50% of their time in the office.

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